1 citations · 1 across the 2 of their papers we have counts for
5 papers
Perspective-Equivariant Fine-tuning for Multispectral Demosaicing without Ground Truth
Andrew Wang, Mike Davies
Multispectral demosaicing is crucial to reconstruct full-resolution spectral images from snapshot mosaiced measurements, enabling real-time imaging from neurosurgery to autonomous…
Benchmarking Self-Supervised Learning Methods for Accelerated MRI Reconstruction
Andrew Wang, Steven McDonagh, Mike Davies
Reconstructing MRI from highly undersampled measurements is crucial for accelerating medical imaging, but is challenging due to the ill-posedness of the inverse problem. While supe…
DeepInverse: A Python package for solving imaging inverse problems with deep learning
Julián Tachella, Matthieu Terris, Samuel Hurault +24
DeepInverse is an open-source PyTorch-based library for solving imaging inverse problems. The library covers all crucial steps in image reconstruction from the efficient implementa…
Fully Unsupervised Dynamic MRI Reconstruction via Diffeo-Temporal Equivariance
Andrew Wang, Mike Davies
Reconstructing dynamic MRI image sequences from undersampled accelerated measurements is crucial for faster and higher spatiotemporal resolution real-time imaging of cardiac motion…
Perspective-Equivariance for Unsupervised Imaging with Camera Geometry
Andrew Wang, Mike Davies
Ill-posed image reconstruction problems appear in many scenarios such as remote sensing, where obtaining high quality images is crucial for environmental monitoring, disaster manag…